Hey cloud enthusiasts, it's time to learn.😀

In this article, I’ll provide a brief overview of Rekognition’s key capabilities and how it can enhance your projects. Amazon Rekognition is a powerful AWS service that enables developers to integrate image and video analysis into their applications. From object detection to facial recognition, it offers a range of AI-powered features that simplify complex tasks.

Rekognition is a service used to find objects, people, text, and scenes in images and videos using machine learning.
It can do facial analysis and facial search to do user verification and people counting in an image.
You can create your database of "familiar faces" or compare them against a database of celebrities to find people in your images as well.
Use cases:

  • labeling images and video

  • content moderation

  • text detection, e.g to see the number of each runner in the race

  • detect faces in an image or video, find facial landmarks such as the position of eyes, and detect emotions such as happy or sad in near-real time or in batches without management of infrastructure or modelling (face detection and analysis)

  • face search and verification

  • celebrity recognition

  • pathing (e.g.:for sports game analysis doing real-time analytics)

Amazon Rekognition-Content Moderation

  • Rekognition is used to detect content that is inappropriate, unwanted, or offensive (images and videos), e.g., racist content or pornography

  • It is used in social media, broadcast media, advertising, and e-commerce situations to create a safer user experience

  • Analyse millions of images, video streams, and stored videos within seconds, and augment human review tasks with AI.

Here is a simple flowchart:
Simple flowchart

  • Amazon Rekognition will analyse the image.

  • You set a minimum confidence threshold for items that will be flagged—the lower the percentage, the more matches you are going to get.
    Confidence percentage represents how confident Rekognition is that this flagged image represents, e.g., an inappropriate or offensive character

  • Once you flagged some images, you may want to do a human manual review.

  • Flagged sensitive content for manual review is done in Amazon Augmented AI (A2I).

  • Manual review helps to know whether you want to keep or delete them. This helps you to comply with regulations before you post your applications.

So there you have it,folks! From building social platforms to preventing grandma from being tagged as a celebrity, Rekognition has you covered. Set those confidence thresholds wisely (or that innocent picture of your cat stretching might raise some eyebrows 😉) and enjoy your machine learning superpowers. Happy Rekognizing! 😎